The present disclosure relates generally to air data systems, and more particularly to air data systems that can utilize artificial intelligence to generate air data outputs for an aircraft.
Modern aircraft often incorporate air data systems that calculate air data outputs based on measured parameters collected from various sensors positioned about the aircraft. For instance, many modern aircraft utilize pneumatic air data probes that measure pitot pressure, static pressure, or other parameters of airflow across the probe. Such pneumatic air data probes often include one or more air data sensing ports, such as static pressure ports and/or total pressure (i.e., stagnation pressure) ports. A portion of air flowing over the probes is diverted to the ports that are pneumatically connected to pressure sensors that sense the atmospheric pressure outside the aircraft. Such measured pressures are usable for determining air data outputs, such as aircraft pressure altitude, altitude rate (e.g., vertical speed), airspeed, Mach number, angle of attack, angle of sideslip, or other air data outputs.
To increase system reliability, aircraft manufacturers typically incorporate redundant (e.g., backup) systems that can provide outputs to consuming systems in the event that a primary system fails or is otherwise determined to be unreliable. For instance, many aircraft incorporate multiple (e.g., two, three, four, or more) pneumatic air data probes, certain of which are designated as backup systems for use when a primary system is deemed unreliable. In some cases, backup systems that utilize dissimilar design architectures and components as compared with a primary system can be desirable to reduce the chances of common mode failures between the primary and backup systems.